Nonlinear stochastic vibration analysis for energy harvesting and other applications
type: CreativeWork
description: With the rapid development of electronic technology, the power consumption of electronic devices has decreased significantly. Consequently, there is substantial interest in harvesting energy from ambient sources, such as vibration, in order to power small-scale wireless devices. To design optimal vibration harvesting systems it is important to determine the maximum power obtainable from a given vibration source. Initially, white noise base excitation of a general nonlinear energy harvester model is considered. The power input from white noise is known to be proportional both to the total oscillating mass of the system and the magnitude of the noise spectral density, regardless of the internal mechanics of the system. This power is split between undesirable mechanical damping and useful electrical dissipation, where the form of the stiffness profile and device parameters determine the relative proportion of energy dissipated by each mechanism. An upper bound on the electrical power is derived and used to guide towards optimal harvesting devices, revealing that low stiffness systems exhibit maximum performance. Many engineering applications will exhibit more complicated spectra than the flat spectrum of white noise. Expanding upon the white noise analysis, a method to investigate the power dissipation of nonlinear oscillators under non-white excitation is developed by extending the Wiener series. The relatively simple first term of the series, together with the excitation spectrum, is found to completely define the power dissipated. An important property of this first term, namely that the integral over its frequency domain representation is proportional to the oscillating mass, is derived and validated both numerically and experimentally, using a base excited cantilever beam with a nonlinear restoring force produced by magnets. Another form of excitation prevalent in many mechanical systems is a combination of deterministic and broadband random vibration. Lastly, the…
abstract: With the rapid development of electronic technology, the power consumption of electronic devices has decreased significantly. Consequently, there is substantial interest in harvesting energy from ambient sources, such as vibration, in order to power small-scale wireless devices. To design optimal vibration harvesting systems it is important to determine the maximum power obtainable from a given vibration source. Initially, white noise base excitation of a general nonlinear energy harvester model is considered. The power input from white noise is known to be proportional both to the total oscillating mass of the system and the magnitude of the noise spectral density, regardless of the internal mechanics of the system. This power is split between undesirable mechanical damping and useful electrical dissipation, where the form of the stiffness profile and device parameters determine the relative proportion of energy dissipated by each mechanism. An upper bound on the electrical power is derived and used to guide towards optimal harvesting devices, revealing that low stiffness systems exhibit maximum performance. Many engineering applications will exhibit more complicated spectra than the flat spectrum of white noise. Expanding upon the white noise analysis, a method to investigate the power dissipation of nonlinear oscillators under non-white excitation is developed by extending the Wiener series. The relatively simple first term of the series, together with the excitation spectrum, is found to completely define the power dissipated. An important property of this first term, namely that the integral over its frequency domain representation is proportional to the oscillating mass, is derived and validated both numerically and experimentally, using a base excited cantilever beam with a nonlinear restoring force produced by magnets. Another form of excitation prevalent in many mechanical systems is a combination of deterministic and broadband random vibration. Lastly, the…
author: Hawes, David
language: en
license: https://www.repository.cam.ac.uk/bitstreams/d161166c-f560-4c52-8793-76d92e7f3fef/download
license: https://www.rioxx.net/licenses/all-rights-reserved/
license: https://www.repository.cam.ac.uk/bitstreams/6077e874-2b81-41ec-91f4-a289efd2d780/download
date published: 2017-01-10
date modified: 2026-07-24T01:33:33Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.6712